[
https://issues.apache.org/jira/browse/SPARK-16571?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Björn-Elmar Macek updated SPARK-16571:
--------------------------------------
Description:
When executing the following code, an exception is thrown.
{code}
val finalProbabilityProxiesDF =
sqlc.sql(app2AgeNormalissationQuery(transformedAppsCol, bucketedAgeCol,
probProxyCol, normFacCol, ageFeatureRawTable, normFactorsTableName,
ageApp2AgeProxyTableName)).repartition(10)
//sort the stats
val finalFeatMap = finalProbabilityProxiesDF.select(transformedAppsCol,
probProxyCol).map{ row =>
val probs =
row.getAs[mutable.WrappedArray[util.ArrayList[Double]]](1).map(array =>
(array.get(0),array.get(1))).toArray
val bucketsExist = probs.map(_._1)
val allBuckets = ageCol match {
case "label" => (0 to ageSplits.size - 1).map(_.toDouble)
case "age" => (1 to ageSplits.size - 2).map(_.toDouble)
}
val missingBuckets = allBuckets.diff(bucketsExist).map{(_, 0.0)}
val fixedProbs = probs ++ missingBuckets
val filteredFixedProbs = ageCol match {
case "label" => fixedProbs
case "age" => fixedProbs.filter(_._1 != 0.0).map(elem => (elem._1 -
1.0, elem._2))
}
val sortedProbs = filteredFixedProbs.sortWith( _._1 < _._1 )
(row.getInt(0), sortedProbs)
}
{code}
The stacktrace shows:
{code}
java.lang.ClassCastException: java.util.ArrayList cannot be cast to
java.lang.Double
at scala.runtime.BoxesRunTime.unboxToDouble(BoxesRunTime.java:114)
at
org.apache.spark.sql.catalyst.util.GenericArrayData.getDouble(GenericArrayData.scala:53)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at
org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
{code}
If i remove the repartition from finalProbabilityProxiesDF the code runs
without problems.
I am unsure about the reasons tho. This should not happen should it?
was:
When executing the following code, an exception is thrown.
{code}
val finalProbabilityProxiesDF =
sqlc.sql(app2AgeNormalissationQuery(transformedAppsCol, bucketedAgeCol,
probProxyCol, normFacCol, ageFeatureRawTable, normFactorsTableName,
ageApp2AgeProxyTableName)).repartition(10)
//sort the stats
val finalFeatMap = finalProbabilityProxiesDF.select(transformedAppsCol,
probProxyCol).map{ row =>
val probs =
row.getAs[mutable.WrappedArray[util.ArrayList[Double]]](1).map(array =>
(array.get(0),array.get(1))).toArray
val bucketsExist = probs.map(_._1)
val allBuckets = ageCol match {
case "label" => (0 to ageSplits.size - 1).map(_.toDouble)
case "age" => (1 to ageSplits.size - 2).map(_.toDouble)
}
val missingBuckets = allBuckets.diff(bucketsExist).map{(_, 0.0)}
val fixedProbs = probs ++ missingBuckets
val filteredFixedProbs = ageCol match {
case "label" => fixedProbs
case "age" => fixedProbs.filter(_._1 != 0.0).map(elem => (elem._1 -
1.0, elem._2))
}
val sortedProbs = filteredFixedProbs.sortWith( _._1 < _._1 )
(row.getInt(0), sortedProbs)
}
{/code}
The stacktrace shows:
{code}
java.lang.ClassCastException: java.util.ArrayList cannot be cast to
java.lang.Double
at scala.runtime.BoxesRunTime.unboxToDouble(BoxesRunTime.java:114)
at
org.apache.spark.sql.catalyst.util.GenericArrayData.getDouble(GenericArrayData.scala:53)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at
org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
{/code}
If i remove the repartition from finalProbabilityProxiesDF the code runs
without problems.
I am unsure about the reasons tho. This should not happen should it?
> DataFrame repartition leads to unexpected error during shuffle
> --------------------------------------------------------------
>
> Key: SPARK-16571
> URL: https://issues.apache.org/jira/browse/SPARK-16571
> Project: Spark
> Issue Type: Bug
> Components: Shuffle
> Affects Versions: 1.6.1
> Reporter: Björn-Elmar Macek
>
> When executing the following code, an exception is thrown.
> {code}
> val finalProbabilityProxiesDF =
> sqlc.sql(app2AgeNormalissationQuery(transformedAppsCol, bucketedAgeCol,
> probProxyCol, normFacCol, ageFeatureRawTable, normFactorsTableName,
> ageApp2AgeProxyTableName)).repartition(10)
> //sort the stats
> val finalFeatMap = finalProbabilityProxiesDF.select(transformedAppsCol,
> probProxyCol).map{ row =>
> val probs =
> row.getAs[mutable.WrappedArray[util.ArrayList[Double]]](1).map(array =>
> (array.get(0),array.get(1))).toArray
> val bucketsExist = probs.map(_._1)
> val allBuckets = ageCol match {
> case "label" => (0 to ageSplits.size - 1).map(_.toDouble)
> case "age" => (1 to ageSplits.size - 2).map(_.toDouble)
> }
> val missingBuckets = allBuckets.diff(bucketsExist).map{(_, 0.0)}
> val fixedProbs = probs ++ missingBuckets
> val filteredFixedProbs = ageCol match {
> case "label" => fixedProbs
> case "age" => fixedProbs.filter(_._1 != 0.0).map(elem => (elem._1 -
> 1.0, elem._2))
> }
> val sortedProbs = filteredFixedProbs.sortWith( _._1 < _._1 )
> (row.getInt(0), sortedProbs)
> }
> {code}
> The stacktrace shows:
> {code}
> java.lang.ClassCastException: java.util.ArrayList cannot be cast to
> java.lang.Double
> at scala.runtime.BoxesRunTime.unboxToDouble(BoxesRunTime.java:114)
> at
> org.apache.spark.sql.catalyst.util.GenericArrayData.getDouble(GenericArrayData.scala:53)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
> Source)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> {code}
> If i remove the repartition from finalProbabilityProxiesDF the code runs
> without problems.
> I am unsure about the reasons tho. This should not happen should it?
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